Embedding Information
From embedding.values() can be calculated the chain size and the longest chain.
From embedding.keys() can be calculated the number of vertices.
Are there other features (information) to be extracted (inferred) from an Embedding?
Comments
Hello,
Sorry for the delay in responding to your question!
The Embedding is a mapping between the Logical Qubits of the problem to the Physical Qubits of the QPU.
It does not have any couple information, but it does tell us which Qubits in the Problem correspond to which Qubits in the Chains.
You can see the length of each individual chain, as well as all of the Qubits in the chains.
Using this information, you could look at the QPU architecture and see exactly where on the QPU the problem is represented.
Another interesting thing you can do is use non-numeric values as the keys.
So your Logical problem Qubits might have labels 'a', 'b', 'c', and they might map to multiple QPU Qubits.
You will be able to see those labels in the embedding.
The embedding is a dictionary which with numerical Logical Qubit labels could look something like this:
{0: [1126, 1118], 1: [1243, 1115, 1246], 2: [1127, 1119, 1120]}
Or with non-numeric Logical Qubit labels could look something like this:
{'a': [1126, 1118], 'b': [1243, 1115, 1246], 'c': [1127, 1119, 1120]}
In these embeddings, the first Logical Qubit corresponds to two Physical Qubits, while the second and third correspond to three each.
I hope this helps to clarify things a little.
Please feel free to ask more questions or for clarification!
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